Optimization-Based Approach for Resilient Connected and Autonomous Intersection Crossing Traffic Control Under V2X Communication

被引:27
作者
Lu, Qiang [1 ]
Jung, Hojin [2 ]
Kim, Kyoung-Dae [2 ]
机构
[1] LG Amer R&D Ctr, Adv Platform Lab, Santa Clara, CA 95054 USA
[2] DGIST, Dept Informat & Commun Engn, Daegu 42988, South Korea
来源
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES | 2022年 / 7卷 / 02期
基金
新加坡国家研究基金会;
关键词
Optimization; Trajectory; Safety; Vehicle-to-everything; Schedules; Delays; Wireless communication; Connected and autonomous vehicle; mixed integer programming (MIP); resilient intelligent intersection management; V2X communication; AUTOMATED VEHICLES; MANAGEMENT;
D O I
10.1109/TIV.2021.3133841
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we present an optimization-based approach for safe, efficient, and resilient autonomous intersection traffic control in realistic vehicle-to-everything (V2X) communication environment. The proposed framework produces the fastest discrete-time trajectory for vehicles who want to cross an intersection. Constraints for safety are designed carefully in the optimization problem formulation to prevent potential collisions during intersection crossings. A novel vehicle-to-intersection (V2I) interaction mechanism is designed to handle imperfect communication characteristics such as packet delivery delay and loss. The proposed intersection management framework is evaluated by running extensive simulations using an open source vehicular network and microscopic traffic simulation software, Veins. The results show that the overall traffic control performance of the proposed framework is substantially better than conventional traffic light control framework, in particular when traffic volume is light and medium, even in situations with a realistic wireless vehicular network setting where packet delivery delays and drops occasionally occur.
引用
收藏
页码:354 / 367
页数:14
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